{smcl}
{com}{sf}{ul off}{txt}{.-}
      name:  {res}<unnamed>
       {txt}log:  {res}C:\Users\sofia.breitenstein\Dropbox\__phd\papers\list experiment\Paper\submission to R&P\Data\log_file.smcl
  {txt}log type:  {res}smcl
 {txt}opened on:  {res}13 Jun 2022, 12:07:10

{com}. do "C:\Users\SOFIA~1.BRE\AppData\Local\Temp\STD3f94_000000.tmp"
{txt}
{com}. use Do_they_really_care.dta, clear 
{txt}
{com}. 
. ******** Analysis ********
. 
. ** Table 1: : Results across different treatment conditions 
. 
. * Means comparison List experiment 
. mean list_short
{res}
{txt}Mean estimation{col 35}Number of obs{col 51}= {res}       400

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 2}list_short {c |}{col 14}{res}{space 2}     2.02{col 26}{space 2} .0457354{col 37}{space 5} 1.930087{col 51}{space 3} 2.109913
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}. mean list_long
{res}
{txt}Mean estimation{col 35}Number of obs{col 51}= {res}       400

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 3}list_long {c |}{col 14}{res}{space 2}    2.845{col 26}{space 2} .0600955{col 37}{space 5} 2.726857{col 51}{space 3} 2.963143
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}. di  2.845  -  2.02 // 82,5% consider corruption reason not to vote for candidate of their preferred party
{res}.825
{txt}
{com}. di 100 - 82.5      // 17,5% do not consider corruption a valid reason for not voting a candidate of their preferred party
{res}17.5
{txt}
{com}. 
. * Results of direct questions 
. tab list_directq  // 22,5% would vote for corrupt politician

 {txt}Imagina un candidato a la alcald�a de {c |}
      tu municipio que tiene una larga {c |}
                             experienc {c |}      Freq.     Percent        Cum.
{hline 39}{c +}{hline 35}
                            Le votar�a {c |}{res}         91       22.75       22.75
{txt}Votar�a a un candidato de otro partido {c |}{res}        153       38.25       61.00
{txt}                            No votar�a {c |}{res}        156       39.00      100.00
{txt}{hline 39}{c +}{hline 35}
                                 Total {c |}{res}        400      100.00
{txt}
{com}.             
.                          
. * Means comparison list experiment for only partisans                    
. 
. mean list_short if partyid!=97
{res}
{txt}Mean estimation{col 35}Number of obs{col 51}= {res}       271

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 2}list_short {c |}{col 14}{res}{space 2}  1.95941{col 26}{space 2} .0520921{col 37}{space 5} 1.856851{col 51}{space 3} 2.061968
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}. mean list_long if partyid!=97
{res}
{txt}Mean estimation{col 35}Number of obs{col 51}= {res}       280

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 3}list_long {c |}{col 14}{res}{space 2} 2.703571{col 26}{space 2} .0694131{col 37}{space 5} 2.566931{col 51}{space 3} 2.840211
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}. di 2.70-1.96                  // 74% consider corruption reason not to vote for candidate of their preferred party
{res}.74
{txt}
{com}. di 100 - 74                   // 26% do not consider corruption a valid reason for not voting a candidate of their preferred party
{res}26
{txt}
{com}. 
. * Results of direct questions with only partisans
.  tab list_directq if partyid!=97  //28,27% would vote for corrupt politician

 {txt}Imagina un candidato a la alcald�a de {c |}
      tu municipio que tiene una larga {c |}
                             experienc {c |}      Freq.     Percent        Cum.
{hline 39}{c +}{hline 35}
                            Le votar�a {c |}{res}         80       28.27       28.27
{txt}Votar�a a un candidato de otro partido {c |}{res}        112       39.58       67.84
{txt}                            No votar�a {c |}{res}         91       32.16      100.00
{txt}{hline 39}{c +}{hline 35}
                                 Total {c |}{res}        283      100.00
{txt}
{com}. 
. 
. * Test wether difference among short and long list is significant 
. recode listexp (1=.), gen(experiment) 
{txt}(400 differences between listexp and experiment)

{com}. generate experiment1= experiment-2
{txt}(400 missing values generated)

{com}. 
. egen float list1 = rowfirst(list_short list_long)
{txt}(400 missing values generated)

{com}. label variable list1 "Items in list experiment"
{txt}
{com}. mean list1, over(experiment) 
{res}
{txt}Mean estimation{col 41}Number of obs{col 57}= {res}       800

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 20}{c |}       Mean{col 32}   Std. Err.{col 44}     [95% Con{col 57}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
c.list1@experiment {c |}
{space 16}2  {c |}{col 20}{res}{space 2}     2.02{col 32}{space 2} .0457354{col 43}{space 5} 1.930224{col 57}{space 3} 2.109776
{txt}{space 16}3  {c |}{col 20}{res}{space 2}    2.845{col 32}{space 2} .0600955{col 43}{space 5} 2.727036{col 57}{space 3} 2.962964
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}. 
. ttest listexp, by(experiment) 

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. Err.{col 47}Std. Dev.{col 59}[95% Conf. Interval]
{hline 9}{c +}{hline 68}
       2 {c |}{res}{col 12}    400{col 22}        2{col 34}        0{col 46}        0{col 58}        2{col 70}        2
       {txt}3 {c |}{res}{col 12}    400{col 22}        3{col 34}        0{col 46}        0{col 58}        3{col 70}        3
{txt}{hline 9}{c +}{hline 68}
combined {c |}{res}{col 12}    800{col 22}      2.5{col 34} .0176887{col 46} .5003128{col 58} 2.465278{col 70} 2.534722
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22}       -1{col 34}        0{col 58}       -1{col 70}       -1
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}2{txt}) - mean({res}3{txt})                                      t = {res}       .
{txt}Ho: diff = 0                                     degrees of freedom = {res}     798

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}     .         {txt}Pr(|T| > |t|) = {res}     .          {txt}Pr(T > t) = {res}     .
{txt}
{com}. 
. 
. ** Table A1: Randomization check: multinomial logit model
. 
. recode education (8=.), gen (edu2)
{txt}(10 differences between education and edu2)

{com}.  
. mlogit listexp i.sex age i.edu2 income ideology partyid 

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-1307.3427}  
Iteration 1:{space 3}log likelihood = {res:-1299.6586}  
Iteration 2:{space 3}log likelihood = {res:-1299.5988}  
Iteration 3:{space 3}log likelihood = {res:-1299.5987}  
{res}
{txt}Multinomial logistic regression{col 49}Number of obs{col 67}= {res}     1,190
{txt}{col 49}LR chi2({res}14{txt}){col 67}= {res}     15.49
{txt}{col 49}Prob > chi2{col 67}= {res}    0.3456
{txt}Log likelihood = {res}-1299.5987{txt}{col 49}Pseudo R2{col 67}= {res}    0.0059

{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}        listexp{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}Direct_question {txt}{c |}
{space 12}sex {c |}
{space 9}Mujer  {c |}{col 17}{res}{space 2}-.0347713{col 29}{space 2} .1453972{col 40}{space 1}   -0.24{col 49}{space 3}0.811{col 57}{space 4}-.3197446{col 70}{space 3} .2502019
{txt}{space 12}age {c |}{col 17}{res}{space 2}-.0073671{col 29}{space 2}  .004826{col 40}{space 1}   -1.53{col 49}{space 3}0.127{col 57}{space 4}-.0168259{col 70}{space 3} .0020917
{txt}{space 15} {c |}
{space 11}edu2 {c |}
{space 13}2  {c |}{col 17}{res}{space 2} .3848867{col 29}{space 2} .4174759{col 40}{space 1}    0.92{col 49}{space 3}0.357{col 57}{space 4}-.4333511{col 70}{space 3} 1.203125
{txt}{space 13}3  {c |}{col 17}{res}{space 2} .4514452{col 29}{space 2} .4223008{col 40}{space 1}    1.07{col 49}{space 3}0.285{col 57}{space 4}-.3762491{col 70}{space 3} 1.279139
{txt}{space 15} {c |}
{space 9}income {c |}{col 17}{res}{space 2}-.0066725{col 29}{space 2} .0198512{col 40}{space 1}   -0.34{col 49}{space 3}0.737{col 57}{space 4}-.0455801{col 70}{space 3} .0322351
{txt}{space 7}ideology {c |}{col 17}{res}{space 2} .0077537{col 29}{space 2} .0291042{col 40}{space 1}    0.27{col 49}{space 3}0.790{col 57}{space 4}-.0492896{col 70}{space 3}  .064797
{txt}{space 8}partyid {c |}{col 17}{res}{space 2}-.0016597{col 29}{space 2} .0016943{col 40}{space 1}   -0.98{col 49}{space 3}0.327{col 57}{space 4}-.0049805{col 70}{space 3} .0016612
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} .0234332{col 29}{space 2} .5210203{col 40}{space 1}    0.04{col 49}{space 3}0.964{col 57}{space 4}-.9977478{col 70}{space 3} 1.044614
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}{res}Short_list     {col 17}{txt}{c |}  (base outcome)
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}Long_list       {txt}{c |}
{space 12}sex {c |}
{space 9}Mujer  {c |}{col 17}{res}{space 2} -.082702{col 29}{space 2} .1456815{col 40}{space 1}   -0.57{col 49}{space 3}0.570{col 57}{space 4}-.3682326{col 70}{space 3} .2028285
{txt}{space 12}age {c |}{col 17}{res}{space 2}-.0057441{col 29}{space 2} .0048266{col 40}{space 1}   -1.19{col 49}{space 3}0.234{col 57}{space 4}-.0152041{col 70}{space 3} .0037159
{txt}{space 15} {c |}
{space 11}edu2 {c |}
{space 13}2  {c |}{col 17}{res}{space 2}-.6063953{col 29}{space 2} .3363276{col 40}{space 1}   -1.80{col 49}{space 3}0.071{col 57}{space 4}-1.265585{col 70}{space 3} .0527947
{txt}{space 13}3  {c |}{col 17}{res}{space 2}-.6056047{col 29}{space 2} .3423931{col 40}{space 1}   -1.77{col 49}{space 3}0.077{col 57}{space 4}-1.276683{col 70}{space 3} .0654735
{txt}{space 15} {c |}
{space 9}income {c |}{col 17}{res}{space 2} .0290405{col 29}{space 2} .0198566{col 40}{space 1}    1.46{col 49}{space 3}0.144{col 57}{space 4}-.0098777{col 70}{space 3} .0679587
{txt}{space 7}ideology {c |}{col 17}{res}{space 2} .0053131{col 29}{space 2} .0291735{col 40}{space 1}    0.18{col 49}{space 3}0.855{col 57}{space 4}-.0518659{col 70}{space 3} .0624922
{txt}{space 8}partyid {c |}{col 17}{res}{space 2}-.0015422{col 29}{space 2} .0016976{col 40}{space 1}   -0.91{col 49}{space 3}0.364{col 57}{space 4}-.0048694{col 70}{space 3} .0017851
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} .6617068{col 29}{space 2} .4612002{col 40}{space 1}    1.43{col 49}{space 3}0.151{col 57}{space 4} -.242229{col 70}{space 3} 1.565643
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}.   
. eststo: mlog listexp i.sex age i.edu2 income ideology partyid 

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-1307.3427}  
Iteration 1:{space 3}log likelihood = {res:-1299.6586}  
Iteration 2:{space 3}log likelihood = {res:-1299.5988}  
Iteration 3:{space 3}log likelihood = {res:-1299.5987}  
{res}
{txt}Multinomial logistic regression{col 49}Number of obs{col 67}= {res}     1,190
{txt}{col 49}LR chi2({res}14{txt}){col 67}= {res}     15.49
{txt}{col 49}Prob > chi2{col 67}= {res}    0.3456
{txt}Log likelihood = {res}-1299.5987{txt}{col 49}Pseudo R2{col 67}= {res}    0.0059

{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}        listexp{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}Direct_question {txt}{c |}
{space 12}sex {c |}
{space 9}Mujer  {c |}{col 17}{res}{space 2}-.0347713{col 29}{space 2} .1453972{col 40}{space 1}   -0.24{col 49}{space 3}0.811{col 57}{space 4}-.3197446{col 70}{space 3} .2502019
{txt}{space 12}age {c |}{col 17}{res}{space 2}-.0073671{col 29}{space 2}  .004826{col 40}{space 1}   -1.53{col 49}{space 3}0.127{col 57}{space 4}-.0168259{col 70}{space 3} .0020917
{txt}{space 15} {c |}
{space 11}edu2 {c |}
{space 13}2  {c |}{col 17}{res}{space 2} .3848867{col 29}{space 2} .4174759{col 40}{space 1}    0.92{col 49}{space 3}0.357{col 57}{space 4}-.4333511{col 70}{space 3} 1.203125
{txt}{space 13}3  {c |}{col 17}{res}{space 2} .4514452{col 29}{space 2} .4223008{col 40}{space 1}    1.07{col 49}{space 3}0.285{col 57}{space 4}-.3762491{col 70}{space 3} 1.279139
{txt}{space 15} {c |}
{space 9}income {c |}{col 17}{res}{space 2}-.0066725{col 29}{space 2} .0198512{col 40}{space 1}   -0.34{col 49}{space 3}0.737{col 57}{space 4}-.0455801{col 70}{space 3} .0322351
{txt}{space 7}ideology {c |}{col 17}{res}{space 2} .0077537{col 29}{space 2} .0291042{col 40}{space 1}    0.27{col 49}{space 3}0.790{col 57}{space 4}-.0492896{col 70}{space 3}  .064797
{txt}{space 8}partyid {c |}{col 17}{res}{space 2}-.0016597{col 29}{space 2} .0016943{col 40}{space 1}   -0.98{col 49}{space 3}0.327{col 57}{space 4}-.0049805{col 70}{space 3} .0016612
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} .0234332{col 29}{space 2} .5210203{col 40}{space 1}    0.04{col 49}{space 3}0.964{col 57}{space 4}-.9977478{col 70}{space 3} 1.044614
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}{res}Short_list     {col 17}{txt}{c |}  (base outcome)
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}Long_list       {txt}{c |}
{space 12}sex {c |}
{space 9}Mujer  {c |}{col 17}{res}{space 2} -.082702{col 29}{space 2} .1456815{col 40}{space 1}   -0.57{col 49}{space 3}0.570{col 57}{space 4}-.3682326{col 70}{space 3} .2028285
{txt}{space 12}age {c |}{col 17}{res}{space 2}-.0057441{col 29}{space 2} .0048266{col 40}{space 1}   -1.19{col 49}{space 3}0.234{col 57}{space 4}-.0152041{col 70}{space 3} .0037159
{txt}{space 15} {c |}
{space 11}edu2 {c |}
{space 13}2  {c |}{col 17}{res}{space 2}-.6063953{col 29}{space 2} .3363276{col 40}{space 1}   -1.80{col 49}{space 3}0.071{col 57}{space 4}-1.265585{col 70}{space 3} .0527947
{txt}{space 13}3  {c |}{col 17}{res}{space 2}-.6056047{col 29}{space 2} .3423931{col 40}{space 1}   -1.77{col 49}{space 3}0.077{col 57}{space 4}-1.276683{col 70}{space 3} .0654735
{txt}{space 15} {c |}
{space 9}income {c |}{col 17}{res}{space 2} .0290405{col 29}{space 2} .0198566{col 40}{space 1}    1.46{col 49}{space 3}0.144{col 57}{space 4}-.0098777{col 70}{space 3} .0679587
{txt}{space 7}ideology {c |}{col 17}{res}{space 2} .0053131{col 29}{space 2} .0291735{col 40}{space 1}    0.18{col 49}{space 3}0.855{col 57}{space 4}-.0518659{col 70}{space 3} .0624922
{txt}{space 8}partyid {c |}{col 17}{res}{space 2}-.0015422{col 29}{space 2} .0016976{col 40}{space 1}   -0.91{col 49}{space 3}0.364{col 57}{space 4}-.0048694{col 70}{space 3} .0017851
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} .6617068{col 29}{space 2} .4612002{col 40}{space 1}    1.43{col 49}{space 3}0.151{col 57}{space 4} -.242229{col 70}{space 3} 1.565643
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
({res}est4{txt} stored)

{com}. esttab using Mlogit_listexp2.rtf, nolabel unstack nomti onecell wide noomitted nogap ///
> label  nonumbers  ///
> starlevels(* 0.05 ** 0.01 *** 0.001) ///
> b(2) se(2) sca(chi2 p) obslast /// 
> addnote("Note: Dependent Variable: listexperiment. Base category: treated") ///
> varlabels(_cons Constant  sex "Gender" age "Age" edu2 "Education" income "income" ideology "ideology" partyid "partisanship")replace 
{res}{txt}(output written to {browse  `"Mlogit_listexp2.rtf"'})

{com}. 
. mlogit  listexp i.sex 

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-1318.3347}  
Iteration 1:{space 3}log likelihood = {res:-1318.2814}  
Iteration 2:{space 3}log likelihood = {res:-1318.2814}  
{res}
{txt}Multinomial logistic regression{col 49}Number of obs{col 67}= {res}     1,200
{txt}{col 49}LR chi2({res}2{txt}){col 67}= {res}      0.11
{txt}{col 49}Prob > chi2{col 67}= {res}    0.9480
{txt}Log likelihood = {res}-1318.2814{txt}{col 49}Pseudo R2{col 67}= {res}    0.0000

{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}        listexp{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}{res}Direct_question{col 17}{txt}{c |}  (base outcome)
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}Short_list      {txt}{c |}
{space 12}sex {c |}
{space 9}Mujer  {c |}{col 17}{res}{space 2} 2.83e-16{col 29}{space 2}  .141485{col 40}{space 1}    0.00{col 49}{space 3}1.000{col 57}{space 4}-.2773056{col 70}{space 3} .2773056
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} 6.84e-17{col 29}{space 2} .1015346{col 40}{space 1}    0.00{col 49}{space 3}1.000{col 57}{space 4}-.1990042{col 70}{space 3} .1990042
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}Long_list       {txt}{c |}
{space 12}sex {c |}
{space 9}Mujer  {c |}{col 17}{res}{space 2}-.0400173{col 29}{space 2} .1414567{col 40}{space 1}   -0.28{col 49}{space 3}0.777{col 57}{space 4}-.3172675{col 70}{space 3} .2372328
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} .0204089{col 29}{space 2} .1010205{col 40}{space 1}    0.20{col 49}{space 3}0.840{col 57}{space 4}-.1775877{col 70}{space 3} .2184054
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. mlogit  listexp age

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-1318.3347}  
Iteration 1:{space 3}log likelihood = {res:-1316.9012}  
Iteration 2:{space 3}log likelihood = {res:-1316.9007}  
Iteration 3:{space 3}log likelihood = {res:-1316.9007}  
{res}
{txt}Multinomial logistic regression{col 49}Number of obs{col 67}= {res}     1,200
{txt}{col 49}LR chi2({res}2{txt}){col 67}= {res}      2.87
{txt}{col 49}Prob > chi2{col 67}= {res}    0.2383
{txt}Log likelihood = {res}-1316.9007{txt}{col 49}Pseudo R2{col 67}= {res}    0.0011

{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}        listexp{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}{res}Direct_question{col 17}{txt}{c |}  (base outcome)
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}Short_list      {txt}{c |}
{space 12}age {c |}{col 17}{res}{space 2}  .007791{col 29}{space 2} .0046191{col 40}{space 1}    1.69{col 49}{space 3}0.092{col 57}{space 4}-.0012624{col 70}{space 3} .0168443
{txt}{space 10}_cons {c |}{col 17}{res}{space 2}-.3530256{col 29}{space 2} .2209506{col 40}{space 1}   -1.60{col 49}{space 3}0.110{col 57}{space 4}-.7860807{col 70}{space 3} .0800296
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}Long_list       {txt}{c |}
{space 12}age {c |}{col 17}{res}{space 2} .0043999{col 29}{space 2} .0046187{col 40}{space 1}    0.95{col 49}{space 3}0.341{col 57}{space 4}-.0046525{col 70}{space 3} .0134523
{txt}{space 10}_cons {c |}{col 17}{res}{space 2}-.1976138{col 29}{space 2} .2191664{col 40}{space 1}   -0.90{col 49}{space 3}0.367{col 57}{space 4} -.627172{col 70}{space 3} .2319445
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. mlogit  listexp i.edu2

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-1307.3427}  
Iteration 1:{space 3}log likelihood = {res:-1303.2643}  
Iteration 2:{space 3}log likelihood = {res:-1303.2042}  
Iteration 3:{space 3}log likelihood = {res:-1303.2041}  
{res}
{txt}Multinomial logistic regression{col 49}Number of obs{col 67}= {res}     1,190
{txt}{col 49}LR chi2({res}4{txt}){col 67}= {res}      8.28
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0819
{txt}Log likelihood = {res}-1303.2041{txt}{col 49}Pseudo R2{col 67}= {res}    0.0032

{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}        listexp{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}Direct_question {txt}{c |}
{space 11}edu2 {c |}
{space 13}2  {c |}{col 17}{res}{space 2} .4459071{col 29}{space 2} .4148975{col 40}{space 1}    1.07{col 49}{space 3}0.282{col 57}{space 4}-.3672771{col 70}{space 3} 1.259091
{txt}{space 13}3  {c |}{col 17}{res}{space 2} .5265169{col 29}{space 2} .4169034{col 40}{space 1}    1.26{col 49}{space 3}0.207{col 57}{space 4}-.2905989{col 70}{space 3} 1.343633
{txt}{space 15} {c |}
{space 10}_cons {c |}{col 17}{res}{space 2}-.4700047{col 29}{space 2} .4031129{col 40}{space 1}   -1.17{col 49}{space 3}0.244{col 57}{space 4}-1.260091{col 70}{space 3} .3200821
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}{res}Short_list     {col 17}{txt}{c |}  (base outcome)
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}Long_list       {txt}{c |}
{space 11}edu2 {c |}
{space 13}2  {c |}{col 17}{res}{space 2}-.5393099{col 29}{space 2}  .332789{col 40}{space 1}   -1.62{col 49}{space 3}0.105{col 57}{space 4}-1.191564{col 70}{space 3} .1129446
{txt}{space 13}3  {c |}{col 17}{res}{space 2}-.4972033{col 29}{space 2} .3356454{col 40}{space 1}   -1.48{col 49}{space 3}0.139{col 57}{space 4}-1.155056{col 70}{space 3} .1606496
{txt}{space 15} {c |}
{space 10}_cons {c |}{col 17}{res}{space 2} .4855072{col 29}{space 2} .3177444{col 40}{space 1}    1.53{col 49}{space 3}0.127{col 57}{space 4}-.1372604{col 70}{space 3} 1.108275
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. mlogit  listexp  income 

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-1318.3347}  
Iteration 1:{space 3}log likelihood = {res:-1316.9322}  
Iteration 2:{space 3}log likelihood = {res:-1316.9318}  
Iteration 3:{space 3}log likelihood = {res:-1316.9318}  
{res}
{txt}Multinomial logistic regression{col 49}Number of obs{col 67}= {res}     1,200
{txt}{col 49}LR chi2({res}2{txt}){col 67}= {res}      2.81
{txt}{col 49}Prob > chi2{col 67}= {res}    0.2459
{txt}Log likelihood = {res}-1316.9318{txt}{col 49}Pseudo R2{col 67}= {res}    0.0011

{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}        listexp{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}{res}Direct_question{col 17}{txt}{c |}  (base outcome)
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}Short_list      {txt}{c |}
{space 9}income {c |}{col 17}{res}{space 2} .0088687{col 29}{space 2}  .019429{col 40}{space 1}    0.46{col 49}{space 3}0.648{col 57}{space 4}-.0292115{col 70}{space 3} .0469488
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} -.071404{col 29}{space 2} .1716719{col 40}{space 1}   -0.42{col 49}{space 3}0.677{col 57}{space 4}-.4078747{col 70}{space 3} .2650668
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}Long_list       {txt}{c |}
{space 9}income {c |}{col 17}{res}{space 2} .0316211{col 29}{space 2} .0194913{col 40}{space 1}    1.62{col 49}{space 3}0.105{col 57}{space 4}-.0065811{col 70}{space 3} .0698233
{txt}{space 10}_cons {c |}{col 17}{res}{space 2}-.2593443{col 29}{space 2} .1748611{col 40}{space 1}   -1.48{col 49}{space 3}0.138{col 57}{space 4}-.6020657{col 70}{space 3} .0833771
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. mlogit listexp ideology

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-1318.3347}  
Iteration 1:{space 3}log likelihood = {res:-1318.3239}  
Iteration 2:{space 3}log likelihood = {res:-1318.3239}  
{res}
{txt}Multinomial logistic regression{col 49}Number of obs{col 67}= {res}     1,200
{txt}{col 49}LR chi2({res}2{txt}){col 67}= {res}      0.02
{txt}{col 49}Prob > chi2{col 67}= {res}    0.9892
{txt}Log likelihood = {res}-1318.3239{txt}{col 49}Pseudo R2{col 67}= {res}    0.0000

{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}        listexp{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}{res}Direct_question{col 17}{txt}{c |}  (base outcome)
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}Short_list      {txt}{c |}
{space 7}ideology {c |}{col 17}{res}{space 2}-.0012395{col 29}{space 2} .0287462{col 40}{space 1}   -0.04{col 49}{space 3}0.966{col 57}{space 4} -.057581{col 70}{space 3}  .055102
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} .0051145{col 29}{space 2} .1380915{col 40}{space 1}    0.04{col 49}{space 3}0.970{col 57}{space 4}-.2655398{col 70}{space 3} .2757689
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}Long_list       {txt}{c |}
{space 7}ideology {c |}{col 17}{res}{space 2} .0028897{col 29}{space 2} .0287338{col 40}{space 1}    0.10{col 49}{space 3}0.920{col 57}{space 4}-.0534275{col 70}{space 3} .0592068
{txt}{space 10}_cons {c |}{col 17}{res}{space 2}-.0119596{col 29}{space 2} .1383562{col 40}{space 1}   -0.09{col 49}{space 3}0.931{col 57}{space 4}-.2831328{col 70}{space 3} .2592136
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. recode partyid (1=1 "PP") (2=2 "PSOE") (3=3 "Podemos") (4=4 "C's") (5/97=.), gen (partisans)
{txt}(643 differences between partyid and partisans)

{com}. 
. mlogit listexp partisans 

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-611.79082}  
Iteration 1:{space 3}log likelihood = {res:-611.30038}  
Iteration 2:{space 3}log likelihood = {res:-611.30027}  
Iteration 3:{space 3}log likelihood = {res:-611.30027}  
{res}
{txt}Multinomial logistic regression{col 49}Number of obs{col 67}= {res}       557
{txt}{col 49}LR chi2({res}2{txt}){col 67}= {res}      0.98
{txt}{col 49}Prob > chi2{col 67}= {res}    0.6123
{txt}Log likelihood = {res}-611.30027{txt}{col 49}Pseudo R2{col 67}= {res}    0.0008

{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}        listexp{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}Direct_question {txt}{c |}
{space 6}partisans {c |}{col 17}{res}{space 2}-.0338868{col 29}{space 2}  .095759{col 40}{space 1}   -0.35{col 49}{space 3}0.723{col 57}{space 4}-.2215711{col 70}{space 3} .1537974
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} .0397596{col 29}{space 2}  .283908{col 40}{space 1}    0.14{col 49}{space 3}0.889{col 57}{space 4}-.5166898{col 70}{space 3}  .596209
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}{res}Short_list     {col 17}{txt}{c |}  (base outcome)
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}Long_list       {txt}{c |}
{space 6}partisans {c |}{col 17}{res}{space 2}-.0930603{col 29}{space 2} .0950561{col 40}{space 1}   -0.98{col 49}{space 3}0.328{col 57}{space 4}-.2793669{col 70}{space 3} .0932462
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} .2217036{col 29}{space 2} .2788414{col 40}{space 1}    0.80{col 49}{space 3}0.427{col 57}{space 4}-.3248155{col 70}{space 3} .7682227
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
{txt}end of do-file

{com}. log close
      {txt}name:  {res}<unnamed>
       {txt}log:  {res}C:\Users\sofia.breitenstein\Dropbox\__phd\papers\list experiment\Paper\submission to R&P\Data\log_file.smcl
  {txt}log type:  {res}smcl
 {txt}closed on:  {res}13 Jun 2022, 12:07:24
{txt}{.-}
{smcl}
{txt}{sf}{ul off}